Hosang Wu - Data Analyst
Hosang Wu is a data analyst in the Food & Agri department at RaboResearch. "All those hundreds of thousands of data points we collect every day benefit the bank, society, and the environment. That makes my work impactful."
“I work on the consumer side. That means I collect data on price increases in supermarkets, among other things. We compare prices of products in the same category and what this means for consumers. You can derive a lot from this that goes directly to the consumer, such as purchasing power.”
“It is not only the consumer who benefits from the conclusions of this data, but also the bank and therefore the producer. This allows us to see where prices have increased or decreased, as well as which products are most commonly purchased. We see that directly in our data. With our long-term analysis, my colleagues can give better advice to producers. Informing and advising the producer about this is a big step in encouraging more transparent and fairer value chains. In this way, we are not only a lender for companies, but also a sparring partner for their business strategy.”
“Healthy eating is an important topic. You can see that, for example, with the Nutri-Score you see on food in supermarkets. That Nutri-Score is intended to help people make healthier choices. Through the data I collect, we can see if people are actually making healthier choices. But I also examine whether a healthier choice is a more expensive choice. I think those are great subjects to work with because all the data I collect is directly reflected on our investments, on producers’ business strategies and consumers’ wallets.”
Do you buy or build data?
“To collect that data, you have to have a clear idea in advance of what your question is. That’s where collaboration comes in with your colleagues and stakeholders, because your objective must be clear. Only then can we start collecting data. And therein lies another challenge for me, because do you buy data or do you build the tools to collect data yourself? I often build tools in Python, because with purchased data you don’t always know what the source is and how the data was collected. Rabobank is innovative and there is plenty of room to propose new ideas. We are very critical of the data we collect and test our tools well. Once we have collected the data to answer our question, we check the margin of error, compare our figures with those of different research agencies, and a final check is made by our industry experts.”
“The informal atmosphere and flat culture at Rabobank make everyone easy and quick to approach. I can work efficiently because of the short lines of communication. I like that. When I started here, of course I still had a lot to learn, and it’s nice when your colleagues support you in that. And still I notice that we really work as a team at Rabobank. It has to be, because Data Science is not an end but a means that benefits the bank, society and the environment. You need that team spirit to drive important, sustainable developments based on that data. I am 100 percent behind that.”